
import numpy as np
import pandas as pd
%matplotlib inline
import seaborn as sns
import matplotlib.pyplot as plt

from ipywidgets import widgets, interact


sns.set(style="darkgrid",)
sns.set_palette('deep')
sns.set_context("talk")


filename = r'Results\CSV\PU\PV_Limite_001.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PU\PV_Limite_007.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0.0, 0.4)]


sns.set_context("paper")
filename = r'Results\CSV\PU\PV_Limite_001.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df['Zero'] = (df['COF']<0.05)
df['T_c'] = df['T']-0.3770
df['X'] = (4.66/2)*np.cos(4*np.pi*df['T_c'])
df['V'] = (4.66/2)*4*np.pi*np.sin(4*np.pi*df['T_c'])

Vmed = 30000/df['T'].max()

ndf = df[abs(df['V'])>Vmed]

df


#df = df.rename(columns={'T':'Tempo (s)', 'COF':'Coeficiente de atrito cinético (-)'})
d = df[(df['Tempo (s)']>705)&(df['Tempo (s)']<706)]
sns.set(font_scale=1.5, rc={"lines.linewidth": 1})
g = sns.relplot(data = d, kind = 'line', x = 'Tempo (s)', y='Coeficiente de atrito cinético (-)')

g.set(ylim=(0, 0.37))

#df['T_r']= df['T'].round(0)

#sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x16780c57288>


filename = r'Results\CSV\PU\PV_Limite_007.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd1c0a0b08>


filename = r'Results\CSV\PU\PV_Limite_002.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PU\PV_Limite_008.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PU\PV_Limite_002.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd1d643308>


filename = r'Results\CSV\PU\PV_Limite_003.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PU\PV_Limite_009.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PU\PV_Limite_003.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd1d6fdd88>


filename = r'Results\CSV\PU\PV_Limite_004.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PU\PV_Limite_010.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PU\PV_Limite_004.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd1d6cc248>


filename = r'Results\CSV\PU\PV_Limite_005.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PU\PV_Limite_011.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PU\PV_Limite_005.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd1df35588>


filename = r'Results\CSV\PU\PV_Limite_006.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PU\PV_Limite_012.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PU\PV_Limite_006.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd1df0dcc8>


filename = r'Results\CSV\PU\PV_Limite_008.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd1d431f88>


filename = r'Results\CSV\PU\PV_Limite_009.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd1df73148>


filename = r'Results\CSV\PU\PV_Limite_010.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd1c04b2c8>


filename = r'Results\CSV\PU\PV_Limite_011.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd209a9a48>


filename = r'Results\CSV\PU\PV_Limite_012.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd220bd048>


filename = r'Results\CSV\PUEG1\PV_Limite_001.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG1\PV_Limite_007.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PUEG1\PV_Limite_001.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd1a036748>


filename = r'Results\CSV\PUEG1\PV_Limite_002.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG1\PV_Limite_010.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PUEG1\PV_Limite_002.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd1d556f88>


filename = r'Results\CSV\PUEG1\PV_Limite_003.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG1\PV_Limite_008.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PUEG1\PV_Limite_003.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd071c15c8>


filename = r'Results\CSV\PUEG1\PV_Limite_004.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG1\PV_Limite_009.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PUEG1\PV_Limite_004.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd0728e508>


filename = r'Results\CSV\PUEG1\PV_Limite_005.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG1\PV_Limite_011.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PUEG1\PV_Limite_005.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd1dfa6948>


filename = r'Results\CSV\PUEG1\PV_Limite_006.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG1\PV_Limite_012.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PUEG1\PV_Limite_006.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd2207e048>


filename = r'Results\CSV\PUEG1\PV_Limite_007.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd22025688>


filename = r'Results\CSV\PUEG1\PV_Limite_008.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd071037c8>


filename = r'Results\CSV\PUEG1\PV_Limite_009.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd0238e188>


filename = r'Results\CSV\PUEG1\PV_Limite_010.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd01ccf048>


filename = r'Results\CSV\PUEG1\PV_Limite_011.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd20925488>


filename = r'Results\CSV\PUEG1\PV_Limite_012.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd030e0388>


filename = r'Results\CSV\PUEG2\PV_Limite_001.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG2\PV_Limite_007.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PUEG2\PV_Limite_001.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd01d23948>


filename = r'Results\CSV\PUEG2\PV_Limite_002.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG2\PV_Limite_011.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PUEG2\PV_Limite_002.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd06778648>


filename = r'Results\CSV\PUEG2\PV_Limite_003.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG2\PV_Limite_009.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PUEG2\PV_Limite_003.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd01c93508>


filename = r'Results\CSV\PUEG2\PV_Limite_004.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG2\PV_Limite_010.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PUEG2\PV_Limite_004.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd023e0988>


filename = r'Results\CSV\PUEG2\PV_Limite_005.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG2\PV_Limite_008.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PUEG2\PV_Limite_005.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd01d2fc08>


filename = r'Results\CSV\PUEG2\PV_Limite_006.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG2\PV_Limite_012.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PUEG2\PV_Limite_006.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd01d00708>


filename = r'Results\CSV\PUEG2\PV_Limite_007.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd09b846c8>


filename = r'Results\CSV\PUEG2\PV_Limite_008.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd0709d0c8>


filename = r'Results\CSV\PUEG2\PV_Limite_009.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd01ce1088>


filename = r'Results\CSV\PUEG2\PV_Limite_010.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd07071ac8>


filename = r'Results\CSV\PUEG2\PV_Limite_011.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd01c85bc8>


filename = r'Results\CSV\PUEG2\PV_Limite_012.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd09a706c8>


filename = r'Results\CSV\PUEG4\PV_Limite_001.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG4\PV_Limite_013.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PUEG4\PV_Limite_001.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd07002c88>


filename = r'Results\CSV\PUEG4\PV_Limite_002.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG4\PV_Limite_004.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')


plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
ax.annotate("Início do steady-state",
            xy=(475, 0.175), xycoords='data',
            xytext=(0, 0.35), textcoords='data',
            size=18,
            arrowprops=dict(arrowstyle = '->',
                            connectionstyle="arc3",
                            facecolor = 'k',
                            edgecolor = 'k'
                           ),
            )
ax.axvline(600, ls='--', color='k')

<matplotlib.lines.Line2D at 0x1678136db08>


filename = r'Results\CSV\PUEG4\PV_Limite_002.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd09ae2708>


filename = r'Results\CSV\PUEG4\PV_Limite_003.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG4\PV_Limite_011.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PUEG4\PV_Limite_003.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd09b830c8>


filename = r'Results\CSV\PUEG4\PV_Limite_004.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd021d9448>


filename = r'Results\CSV\PUEG4\PV_Limite_005.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd022a6148>


filename = r'Results\CSV\PUEG4\PV_Limite_006.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd09c4fd48>


filename = r'Results\CSV\PUEG4\PV_Limite_007.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG4\PV_Limite_009.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PUEG4\PV_Limite_007.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd02142588>


filename = r'Results\CSV\PUEG4\PV_Limite_008.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG4\PV_Limite_012.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


filename = r'Results\CSV\PUEG4\PV_Limite_008.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd06f56388>


filename = r'Results\CSV\PUEG4\PV_Limite_009.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd06f510c8>


filename = r'Results\CSV\PUEG4\PV_Limite_010.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd06e756c8>


filename = r'Results\CSV\PUEG4\PV_Limite_011.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd09ab0288>


filename = r'Results\CSV\PUEG4\PV_Limite_012.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd20a24148>


filename = r'Results\CSV\PUEG4\PV_Limite_013.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd11e0d8c8>


filename = r'Results\CSV\PUEG4\PV_Limite_014.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG4\PV_Limite_015.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])

df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']

df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))

[(0, 0.4)]


df.tail(1615048//4)['COF (-)'].describe()

count    403762.000000
mean          0.144294
std           0.044454
min           0.000000
25%           0.113000
50%           0.145000
75%           0.179000
max           0.273000
Name: COF (-), dtype: float64


filename = r'Results\CSV\PUEG4\PV_Limite_014.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd21f76188>


filename = r'Results\CSV\PUEG4\PV_Limite_015.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd11e04cc8>


filename = r'Results\CSV\PUEG4\PV_Limite_016.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])

df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')

df['T_r']= df['T'].round(0)

sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')

<seaborn.axisgrid.FacetGrid at 0x1dd209bcc88>

	Tempo (s)	Fx	Fz	Z	X	Ff	Coeficiente de atrito cinético (-)	Zero	T_c	V
0	0.0000	-0.054	-2.563	-0.0100	5.855312e-02	0.054	0.021	True	-0.3770	29.270397
1	0.0010	-0.075	-2.580	-0.0100	2.927887e-02	0.075	0.029	True	-0.3760	29.277332
2	0.0020	-0.102	-2.600	-0.0105	-4.280141e-16	0.102	0.039	True	-0.3750	29.279644
3	0.0030	-0.119	-2.628	-0.0105	-2.927887e-02	0.119	0.045	True	-0.3740	29.277332
4	0.0040	-0.127	-2.653	-0.0105	-5.855312e-02	0.127	0.048	True	-0.3730	29.270397
...	...	...	...	...	...	...	...	...	...	...
1615044	1615.0439	-0.727	-2.623	0.0035	-1.170912e+00	0.727	0.277	False	1614.6669	25.313880
1615045	1615.0450	-0.740	-2.649	0.0035	-1.198644e+00	0.740	0.279	False	1614.6680	25.108075
1615046	1615.0460	-0.744	-2.665	0.0035	-1.223657e+00	0.744	0.279	False	1614.6690	24.916815
1615047	1615.0470	-0.697	-2.618	0.0035	-1.248476e+00	0.697	0.266	False	1614.6700	24.721621
1615048	1615.0480	-0.667	-2.567	0.0035	-1.273099e+00	0.667	0.260	False	1614.6710	24.522522

PU / 2.5N / 2Hz¶

PU / 2.5N / 2Hz¶

PU / 2.5N / 4Hz¶

PU / 5N / 2Hz¶

PU / 5N / 4Hz¶

PU / 8N / 2Hz¶

PU / 8N / 4Hz¶

PU / 2.5N / 4Hz¶

PU / 5N / 2Hz¶

PU / 5N / 4Hz¶

PU / 8N / 2Hz¶

PU / 8N / 4Hz¶

PUEG1 / 8N / 4Hz¶

PUEG1 / 5N / 2Hz¶

PUEG1 / 5N / 4Hz¶

PUEG1 / 2.5N / 4Hz¶

PUEG1 / 2.5N / 2Hz¶

PUEG1 / 8N / 2Hz¶

PUEG1 / 8N / 4Hz¶

PUEG1 / 5N / 4Hz¶

PUEG1 / 2.5N / 4Hz¶

PUEG1 / 5N / 2Hz¶

PUEG1 / 2.5N / 2Hz¶

PUEG1 / 8N / 2Hz¶

PUEG2 / 5N / 4Hz¶

PUEG2 / 5N / 2Hz¶

PUEG2 / 2.5N / 2Hz¶

PUEG2 / 2.5N / 4Hz¶

PUEG2 / 8N / 4Hz¶

PUEG2 / 8N / 2Hz¶

PUEG2 / 5N / 4Hz¶

PUEG2 / 8N / 4Hz¶

PUEG2 / 2.5N / 2Hz¶

PUEG2 / 2.5N / 4Hz¶

PUEG2 / 5N / 2Hz¶

PUEG2 / 8N / 2Hz¶

PUEG4 / 2.5N / 2Hz¶

PUEG4 / 2.5N / 4Hz¶

PUEG4 / 5N / 4Hz¶

PUEG4 / 2.5 N / 2Hz¶

PUEG4 / 5.17 N / 3Hz¶

PUEG4 / 5.17N / 3Hz¶

PUEG4 / 8N / 2Hz¶

PUEG4 / 8N / 4Hz¶

PUEG4 / 8N / 2 Hz¶

PUEG4 / 5.17N / 3Hz¶

PUEG4 / 5N / 4Hz¶

PUEG4 / 8N / 4Hz¶

PUEG4 / 2.5N / 2Hz¶

PUEG4 / 5N / 2Hz¶

PUEG4 / 5N / 2Hz¶

PUEG4 / 5.17N / 3Hz¶